# GPT-4 Turbo vs Mistral Small

> Mistral Small is the stronger model overall, scoring 33.1 to 30.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-4-turbo-vs-mistral-small
- Last updated: 2026-10-10
- Shared benchmarks: 26

## Summary

- They share 26 benchmarks with published results for both. GPT-4 Turbo scores higher in 0 categories and Mistral Small in 9 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Mistral Small leads 15.4 to 8.6.
- The biggest single-benchmark swing is BigCodeBench Instruct: 48.2% for GPT-4 Turbo and 36.1% for Mistral Small.
- Mistral Small is cheaper at $0.15 / $0.60 per million input/output tokens, against $10 / $30 for GPT-4 Turbo.
- Mistral Small accepts more context: 256K tokens versus 128K.
- Mistral Small has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-4 Turbo | Mistral Small |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 30.3 | 33.1 |
| Rank | 281 | 238 |
| Context | 128K | 256K |
| Input $/M | $10 | $0.15 |
| Output $/M | $30 | $0.60 |
| Weights | Proprietary | Open |

## Coding

- GPT-4 Turbo: 33.4 (#247)
- Mistral Small: 33.5 (#242)

| Benchmark | GPT-4 Turbo | Mistral Small |
|---|---|---|
| BigCodeBench Instruct | 48.2% | 36.1% |
| LMArena Coding | 1268 | 1363 |
| BigCodeBench Complete | 58.2% | 46.6% |
| SciCode | — | 26.5% |
| WeirdML | 18% | — |
| LiveBench Coding | — | 36.2% |
| ALE-Bench | — | 497.62 |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73.3% | — |

## Agentic & Tool Use

- GPT-4 Turbo: —
- Mistral Small: 27.9 (#87)

| Benchmark | GPT-4 Turbo | Mistral Small |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.1% |
| METR Time Horizons | 36.7% | — |

## Reasoning

- GPT-4 Turbo: 14.9 (#311)
- Mistral Small: 19.3 (#238)

| Benchmark | GPT-4 Turbo | Mistral Small |
|---|---|---|
| LMArena Hard Prompts | 1251 | 1336 |
| DTBench | 61.6% | 70.9% |
| LMCA | 9.8% | 20.6% |
| SimpleBench | 25.1% | — |
| Kagi LLM Benchmark | — | 37.8% |
| CritPt | — | 0% |
| Chess Puzzles | 6% | — |
| LiveBench Reasoning | — | 44.8% |
| LiveBench Data Analysis | — | 53.7% |
| Epoch Capabilities Index | 127.25 | — |
| ForecastBench | 59.4 | — |
| LiveBench | — | 44% |

## Math

- GPT-4 Turbo: 8.6 (#316)
- Mistral Small: 15.4 (#287)

| Benchmark | GPT-4 Turbo | Mistral Small |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 6.7% | 5.8% |
| LMArena Math | 1272 | 1341 |
| MATH Level 5 | 46.7% | 46.8% |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| LiveBench Math | — | 39.9% |

## Knowledge

- GPT-4 Turbo: 24.3 (#263)
- Mistral Small: 30.9 (#214)

| Benchmark | GPT-4 Turbo | Mistral Small |
|---|---|---|
| GPQA Diamond | 46.6% | 47.5% |
| LMArena Expert | 1223 | 1293 |
| MMLU | 81.3% | 68.7% |
| Confabulations | 28.4% | — |
| Vectara Hallucination Rate | — | 5.1% |

## Multimodal

- GPT-4 Turbo: 30.0 (#104)
- Mistral Small: 32.9 (#91)

| Benchmark | GPT-4 Turbo | Mistral Small |
|---|---|---|
| LMArena Vision | 1090 | 1142 |

## Multilingual

- GPT-4 Turbo: 40.7 (#211)
- Mistral Small: 45.7 (#164)

| Benchmark | GPT-4 Turbo | Mistral Small |
|---|---|---|
| LMArena Non-English | 1245 | 1315 |
| LMArena Chinese | 1242 | 1342 |
| LMArena French | 1275 | 1337 |
| LMArena German | 1259 | 1341 |
| LMArena Japanese | 1194 | 1275 |
| LMArena Korean | 1187 | 1260 |
| LMArena Russian | 1259 | 1324 |
| LMArena Spanish | 1260 | 1346 |

## Instruction Following

- GPT-4 Turbo: 66.0 (#211)
- Mistral Small: 66.6 (#204)

| Benchmark | GPT-4 Turbo | Mistral Small |
|---|---|---|
| LMArena Instruction Following | 1250 | 1310 |
| LiveBench Instruction Following | — | 63.7% |

## Long Context

- GPT-4 Turbo: 38.0 (#200)
- Mistral Small: 40.4 (#151)

| Benchmark | GPT-4 Turbo | Mistral Small |
|---|---|---|
| LMArena Longer Query | 1254 | 1327 |

## Writing & Preference

- GPT-4 Turbo: 47.9 (#201)
- Mistral Small: 52.6 (#165)

| Benchmark | GPT-4 Turbo | Mistral Small |
|---|---|---|
| LMArena Text | 1272 | 1338 |
| LMArena Creative Writing | 1269 | 1304 |
| LMArena Multi-Turn | 1267 | 1344 |
| LiveBench Language | — | 30.5% |

## FAQ

### Is GPT-4 Turbo better than Mistral Small?

Mistral Small is the stronger model overall, scoring 33.1 to 30.3 on the Noometry Index.

### Which is cheaper, GPT-4 Turbo or Mistral Small?

Mistral Small is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GPT-4 Turbo lists at $10 and $30.

### Is GPT-4 Turbo or Mistral Small better for coding?

They score almost the same on coding (33.4 vs 33.5); test both on your own repository before choosing.

### Which has the bigger context window?

Mistral Small does, with 256K tokens against 128K.

### How many benchmarks do GPT-4 Turbo and Mistral Small share?

26 benchmarks have published results for both models. GPT-4 Turbo has 36 scored results on Noometry and Mistral Small has 39.